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Browse files- README.md +34 -0
- adapter_config.json +43 -0
- adapter_model.safetensors +3 -0
README.md
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---
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library_name: peft
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base_model: Salesforce/codegen-350M-multi
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tags:
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- lora
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- peft
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- code
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- text2sql
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- codegen
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pipeline_tag: text-generation
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---
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# codegenstudio/codegen-350M-text2sql-lora
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LoRA adapter for **text2sql** on [Salesforce/codegen-350M-multi](https://huggingface.co/Salesforce/codegen-350M-multi).
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- Checkpoint version: `v2`
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- Task: `text2sql`
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## Usage
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```python
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from peft import PeftModel
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from transformers import AutoModelForCausalLM, AutoTokenizer
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base = "Salesforce/codegen-350M-multi"
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adapter = "codegenstudio/codegen-350M-text2sql-lora"
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tokenizer = AutoTokenizer.from_pretrained(base)
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model = AutoModelForCausalLM.from_pretrained(base)
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model = PeftModel.from_pretrained(model, adapter)
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```
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Or use the multi-adapter API in this project's `hf-deploy/` package.
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adapter_config.json
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{
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"alora_invocation_tokens": null,
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"alpha_pattern": {},
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"arrow_config": null,
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"auto_mapping": null,
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"base_model_name_or_path": "Salesforce/codegen-350M-multi",
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"bias": "none",
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"corda_config": null,
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"ensure_weight_tying": false,
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"eva_config": null,
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"exclude_modules": null,
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"fan_in_fan_out": false,
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"inference_mode": true,
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"init_lora_weights": true,
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"layer_replication": null,
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"layers_pattern": null,
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"layers_to_transform": null,
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"loftq_config": {},
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"lora_alpha": 32,
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"lora_bias": false,
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"lora_dropout": 0.05,
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"lora_ga_config": null,
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"megatron_config": null,
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"megatron_core": "megatron.core",
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"modules_to_save": null,
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"peft_type": "LORA",
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"peft_version": "0.19.1",
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"qalora_group_size": 16,
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"r": 16,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"qkv_proj",
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"out_proj"
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],
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"target_parameters": null,
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"task_type": "CAUSAL_LM",
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"trainable_token_indices": null,
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"use_bdlora": null,
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"use_dora": false,
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"use_qalora": false,
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"use_rslora": false
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}
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adapter_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:3123afdfba0bd36d6e30834e76d296cbc4f60f1e1ca77b532470d0e881037c9a
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size 7874776
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